Top Artificial Intelligence Jobs in Rome

Lead the AI engineering team to develop and implement AI solutions, mentoring staff, collaborating with business units, and promoting AI adoption.

As a Customer Support Expert, you'll assist brands by offering customer support via social media and email, responding to inquiries, and ensuring positive customer experiences.

As a Senior AI Deployment Engineer, you'll develop and deploy AI software on cloud and edge devices, optimize AI models, and work with microservices and MLOps.

Lead a team of AI engineers to drive innovations in healthcare technology, focusing on NLP and ML methodologies, while contributing hands-on to development.

Provide technical support for AI inference issues, troubleshoot deployment problems, analyze logs/metrics, and enhance platform usability by collaborating with engineering.

As a Senior AI Engineer, you'll design, build, and scale AI agents for restaurant management, improving operations through innovative technology and practices.

This role involves architecting and building AI agent systems, developing full-stack features, and shaping the technical direction of an early-stage startup's AI platform.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

As an AI/ML Specialist Solutions Architect, you will design scalable AI solutions, manage AI deployments, and collaborate with clients to enhance customer satisfaction.

The role combines designing AI/ML architectures and hands-on engineering on AWS. Responsibilities include client requirements gathering, cloud architecture design, and implementing CI/CD for AI workloads.

The Director Analyst will create valuable research for clients in cybersecurity, analyze market trends, and support sales efforts with insights and presentations.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Lead the development of LLM-powered solutions, ensuring scalability and security. Oversee AI system integration and collaboration with various teams.

As a Senior Site Reliability Engineer, you will enhance the reliability and performance of our inference platform, leveraging Kubernetes and Terraform while ensuring smooth scalability of systems under load.

Lead design and implementation of complex open-source AI solutions, provide technical guidance, engage with clients, and contribute to open-source communities.

The Senior Solutions Architect will work on deploying and optimizing AI workloads on GPU clusters, troubleshoot performance issues, and assist customers with advanced AI training solutions.

As a Senior AI Engineer, you will develop AI-based features for workflow automation, collaborate across teams, and drive innovations with LLMs and prompt engineering.

Lead AI strategy and execution at Pigment, mentor a team in AI and data science, and drive AI integration across the organization.

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

WunderGraph seeks a Staff FullStack AI Engineer to lead architecture for AI-driven projects, mentoring engineers and ensuring scalable, secure systems. Responsibilities include backend and frontend development with a focus on AI workflows and enterprise readiness.

The Machine Learning Engineer will architect and develop an AI platform for scientific workflows, integrating autonomous agents, and collaborating with cross-functional teams on ML/AI systems.

The Director of Operations/Strategy will lead strategic planning, facilitate cross-functional coordination, and represent the cofounder in various executive initiatives.

The AI/ML Engineer will develop and maintain AI algorithms, create data pipelines, collaborate on product features, and ensure a high-quality customer experience.

The AI Research Scientist will drive advancements in AI through generative modeling, reinforcement learning, and multimodal reasoning, contributing to impactful research and publications.

Applied AI Engineers will define and deliver AI systems for clients, shape AI visions, build products, and advance the core product using real-world data.